Performance Persistence of Monthly Returns across Strategies: a Study of Asian Hedge funds

1. Performance Persistence of Monthly Returns across Strategies: a Study of Asian Hedge funds By M. O. Sy (RMIT – Melbourne, Australia) L.T. P. Nguyen (MMU, Malaysia) C. M. Yu (MMU, Malaysia)

2. Table of Contents • Objectives of the study • Our Research Problem • Related Literatures • Our Research Methodology • EurekaHedge Database • Sample period • Sampling method • Results • Key Conclusions

3. Table of Contents • Objectives of the study • Research Problem • Related Literatures • Our Research Methodology • Sample period • Sampling method • Results • Key Conclusions

4. Objectives of the Study • To investigate the performance persistence of Asian hedge funds in their returns across strategies over two consecutive months

5. Table of Contents • Objectives of the study • Our Research Problem • Related Literatures • Our Research Methodology • Sample period • Sampling method • Results • Key Conclusions

6. Our Research Problem • Most of studies on performance persistence have done for the American and European hedge funds, but not many have done for Asian hedge funds. • Evidence of persistence of a fund’s performance is very important to investors in making their optimal investment decision. • Results are mixed through literatures for hedge funds. And for Asian hedge funds, limited studies are done.

7. Table of Contents • Objectives of the study • Our Research Problem • Related Literatures • Our Research Methodology • Sample period • Sampling method • Results • Key Conclusions

8. Related Literatures • Hedge Funds’ return persist: Edwards and Caglayan (2001), Harri and Brorsen (2002), Francis, Winston, and Melvyn (2003), Brown and Goetzmann (2001) • Hedge fund returns persistence is in a short-term: Harri and Brorsen (2004), Francis, Winston, and Melvyn (2003) • Performance persistence in risks for hedge funds: Herzberg and Mozes (2003), Kat and Menex (2003) • No evidence of performance persistence in hedge funds: Ennis, Richard, Sebastian, Michael (2003)

9. Table of Contents • Objectives of the study • Our Research Problem • Related Literatures • Our Research Methodology • EurekaHedge Database • Sample period • Sampling method • Results • Key Conclusions

10. EurekaHedge Database 1999 - 2005

11. EurekaHedge Database 1999 - 2005

12. Our Research Methodology • Sample: 661 Asian hedge funds from 12 hedge fund strategies. • Sample data: Net of fee monthly returns • Sample period: January 1999 to December 2005 (84 months of observation). • Two considerations: • Result obtained from each strategy should represent the whole population of funds in that strategy. • The performance of funds should be observed long enough to generalize the persistence in performance of each strategy overtime. • To comply with the above two, we decided to observe the persistence for each strategy through 4 sub-sample periods as well as full sample period. • Subsamples: Jan. 1999 – Dec. 2000, Jan. 2001 – Dec. 2002, Jan. 2003 – Dec. 2004, and Jan. 2005 – Dec. 2005. • Full sample: Jan. 1999 – Dec. 2005.

13. Our Research Methodology • Methods of testing - Agarwal & Naik (2000), Herzberg and Mozes (2003), Harri & Brorsen (2002), Kat & Menexe (2002) and Francis, Winston and Melvyn (2003) : • - Parametric (contigency table) • - Non-Parametric (regression – based model)

14. Parametric – Contingency Table • Cross Product Ratio (CPR) – Christensen 1990 • CPR = (WW * LL)/ (WL * LW) • WW: win in the first month and win in the second month • LL: lose in the first month and lose in the second month • WL: win in the first month and lose in the second month • LW: lose in the first month and win in the second month • Ho: there is no persistence in performance of funds return; or • CPR = 1

15. Parametric – Contingency Table • Test statistics: • (1) Z = ln(CPR)/ ln(CPR) • ln(CPR) = 1/ WW + 1/WL + 1/LW + 1/LL • Z - critical value: 1.96 (5% level of significance)

16. (WW – D1)2 (WL – D2)2 (LW – D3)2 (LL – D4)2 χ2 = + + + D1 D2 D4 D3 where (LW + LL)*(WW + LW) (WW + WL)*(WW + LW) D1 = D3= N N (LW + LL)*(WL + LL) (WW + WL)*(WL + LL) D4 = D2 = N N N = WW + WL + LW + LL Parametric – Contingency Table (2) Chi-square Statistics Critical value: 3.84 (5% level) and 6.63 (1% level)

17. Table of Contents • Objectives of the study • Our Research Problem • Related Literatures • Our Research Methodology • EurekaHedge Database • Sample period • Sampling method • Results • Key Conclusions

19. Non-Parametric – Contingency Table • Cross – sectional regression – Gujarati 2003 • r it= 1+ kDk + 1.ri(t-1) + k.Dk.ri(t-1) + it • where • i = 1,…,n • K = 2,…n • t = 1,…,T • it N(0,2it) • D: dummy, : intercept, : slope coefficient for fund 1, : slope coefficient for fund 2, 3, …., n.

21. Results for CPRs and Slope Coefficient • For arbitrage, results suggest that persistence in performance does not exist for this strategy. However, it is not significant for the whole sample period. • For convertible arbitrage, results are available for full sample and two sub-periods. The positive slope coefficient for the regression line of this strategy suggests that there is no significant evidence of performance persistence for convertible arbitrage. While results for CPRs are not available for CTA, regression model gives some insight of this strategy’s performance. For full sample and sub-sample of 2001- 2002, results suggest that there is significant non-persistence for this strategy. • For long /short equities, results produced for whole sample period suggest that long short equities strategy does not have significant persistent. This might be due to the small number of funds selected for this sample, i.e. 30 funds. However, in our sub-sample for 2005, results show significant persistence for this strategy, which is similar to that obtained from CPRs. The number of fund in this sub-sample period is much larger, i.e. 303 funds.

22. Results for CPRs and Slope Coefficient • For event driven results of regression analysis are similar to those from the previous test. • Compared to the results obtained from CPRs, results from regression method for distressed securities, macro, multi-strategy, and relative values show more significant evidences of their performance persistence. • CPRs results are more in favor of strategies such as event driven and fixed income for all sub-sample periods. However, for full sample period, these strategies show significant evidence of persistence in overall.

23. Keyed Conclusions • With cross-sectional regression, there are more significant evidences of performance persistence for Contingency Table for DISTRESSED DEBT, RELATIVE VALUE, EVENT DRIVEN, and MULTISTRATEGY, compared to those obtained from CPRs. However, there are less significant evidences for FIXED INCOME and EVENT DRIVEN. • In both test, strategies show significant persistence in returns are DISTRESSED DEBT, EVENT DRIVEN, FIXED INCOME, AND MULTI-STRATEGIES. • Mixed results for LONG/SHORT EQUITIES AND MACRO